Method for the location of mobile terminals, related systems and terminal, computer program products thereof

ABSTRACT

A method for determining the location coordinates of a mobile terminal with respect to reference elements adapted to send toward the mobile terminal radioelectric signals involves the steps of measuring the radioelectric signals to derive respective measurements, the measurements being affected by measurement errors, and subjecting the measurements to state-based statistical filtering, such as, a Kalman filtering, to derive therefrom the location coordinates of the mobile terminal. At least some of the reference elements are terrestrial reference elements and in the statistical filtering at least one further state is included in addition to the coordinates. The further state is representative of the measurement errors. The terminal is adapted to be mounted on a vehicle, such as, a motorcar, and to have associated therewith a measurement source, such as, an altimeter adapted to provide additional measurements indicative of the location, e.g., the altitude, and/or the displacement of the mobile terminal.

CROSS REFERENCE TO RELATED APPLICATION

This application is a national phase application based onPCT/EP2003/006381, filed Jun. 17, 2003, the content of which isincorporated herein by reference.

1. Field of the Invention

The present invention relates to techniques for the location of mobileunits or terminals.

2. Description of the Related Art

A number of techniques are known in the art that permit the location ofmobile units in a given area; exemplary of such a system is thesatellite-based positioning system known as the Global PositioningSystem (GPS).

Other arrangements exploit the features of certain terrestrialcommunication systems, such as cellular mobile telecommunicationsystems, for the location of mobile terminals.

Most location systems known in the art operate by taking distancemeasurements with respect to absolute references (or measurements, suchas propagation time measurements of radio-frequency signals, that can berelated to distance measurements), this approach being common both tosatellite-based networks (such as GPS) and “terrestrial” networks.

Satellite-based location systems are also known that exploit differenttypes of measurements with respect to those considered in the foregoinge.g. the displacement over a given time of the mobile system to belocated. These additional measurements have the purpose of improving theaccuracy of the location action.

Statistical filters have also been used in satellite-based locationsystems and most modern GPS receivers include a statistical filter. Therelated technical literature is quite extensive and includes a highnumber of scientific publications and patent publications as well.

Statistical filters have also been recently proposed for use interrestrial-based location systems, as witnessed e.g. by EP-A-1 102 398and EP-A-1 102 399.

Specifically, the arrangement disclosed in EP-A-1 102 398 includes astandard Kalman filter for use in a mixed satellite-based/terrestrialsystem. The same arrangement also takes advantage of statistical methodsfor pre-validating measurements, methods that associate to themeasurements (taken individually or jointly) a degree of likelihood and,finally, methods for computing state innovations.

The arrangement disclosed in EP-A-1 102 399 is a further developmentover the arrangement described in EP-A-1 102 398 that includes ageneralized use of statistical filters. These are used for determining asequence of state estimates, these states representing the motion of theobject to be located. As regards to the Kalman filter, also the“extended” form, for use in non-linear systems, was described. The samedocument additionally describes the use of statistical filters withinpurely terrestrial systems (such as Global System for Mobilecommunications (GSM) and Universal Mobile Telecommunications System(UMTS)) in addition to mixed satellite-terrestrial systems. Also, EP-A-1102 399 indicates the possibility of dispensing with statistical methodsfor pre-validating measurements, which are presented as mandatory inEP-A-1 102 398.

To sum up, the prior art considered in the foregoing broadly andgenerally discloses the possible use of statistical filters (such as aKalman filter) in location systems, such a disclosure applying to anykind of location system whose operation is based on measurements derivedfrom terrestrial or satellite-based networks.

The prior art considered in the foregoing leaves however at least twobasic problems unsolved.

As a first point, statistical filters intrinsically reduce in an optimalway measurement errors and any kind of environment-related error underthe assumption that these errors have a well-known statisticaldistribution (in the case of Kalman filter, errors having a Gaussiandistribution with a zero average or mean value are assumed). Experiencesshow however that when such arrangement are used in the case ofmeasurements related to terrestrial cellular networks, the performanceof the statistical filters is appreciably diminished to the point ofmaking the use of such statistical filters practically useless.

Additionally, not unlike satellite-based systems (that may suffer frompoor reception or lack of reception, i.e. lack of “visibility” ofsatellites in urban canyons and indoor), terrestrial systems may also beadversely affected by phenomena such as multipath or insufficient fieldstrength, these phenomena possibly leading to environments where signalsfrom both satellite-based and terrestrial location systems can be hardlyreceived or are not received at all.

OBJECT AND SUMMARY OF THE INVENTION

The need therefore exists for arrangements that may improve the accuracyof the location action when the above-mentioned standard hypotheses onthe statistical distribution of the measurement errors in statisticalfilters of conventional type are not met: as explained in the foregoing,this is the case of location effected by means of terrestrial cellularnetworks.

The need also exists for arrangements that may improve the accuracy inthe location action in those geographical areas where signals fromlocation system—of the terrestrial type or the satellite-basedtype—cannot be received satisfactorily.

The object of the present invention is to satisfy these needs.

According to the present invention, such an object is achieved by meansof a method having the features set forth in the claims that follow. Theinvention also relates to corresponding system and a terminal for usetherein, as well as a computer program product loadable in the memory ofat least one computer and including software code portions forperforming the method of the invention and/or implementing a terminalaccording to the invention when the product is run on a computer.

The invention lends itself to be implemented in a variety of differentembodiments. These may range from a basic arrangement applied to aterrestrial-based location system and involving the use of an improvedstatistical filtering process, to more sophisticated arrangements thatuse an improved statistical filtering process within the framework of alocation system using both satellite-based and terrestrial-basedreference elements, in possible combination with additional measurementsindicative e.g. of the altitude and/or the displacement (speed,acceleration, and so on.) of the mobile terminal. Still anotherembodiment of the invention may provide a location system using bothsatellite-based and terrestrial-based reference elements, in combinationwith additional measurements and a standard statistical filteringprocess.

A particularly preferred embodiment of the invention is a terminal foruse in a vehicle such as a motorcar in a possible combination with a GPSreceiver.

Essentially, the location system described herein is based on the use ofstatistical filters (hereinafter reference will be steadily made to aKalman filter as exemplary of such types of filters or estimators)wherein, differently from the prior art considered in the foregoing, thesystem states include, in addition to information concerning the motionof the object to be located (for instance its location and speed) aplurality of states that are integrated in the statistical filters inorder to optimize the accuracy of the location action. This also inthose cases where the measurement errors in the networks havestatistical distributions different from those typically hypothesized inthe literature.

Preferably, the invention also provides for the optional use ofadditional measurements with respect to the measurements typicallyperformed in terrestrial and/or satellite-based networks. Theseadditional measurements (such as acceleration measurements) are providedby specific devices and adapted to improve the accuracy of the locationaction. Use of these additional measurements is established in the areaof satellite-based systems, such as a GPS navigator: there, forinstance, the location system is provided with information, concerningthe distance over which the vehicle has traveled and this information,together with cartographic information, makes the location systemsignificantly more accurate in comparison with respect to thosesituations where only the basic measurements provided in the GPS systemsare used.

A preferred embodiment of arrangement disclosed herein provides formeasurements to be carried out on signals from one or more base stationsin a terrestrial cellular networks (for instance a GSM network) and,optionally, from base stations of a satellite-based system (such as GPS)with the possible optional use of additional information concerningmovement of the system to be tracked as provided, for instance byaccelerometers and altimeters.

As indicated, a preferred embodiment of the arrangement shown herein isbased on the use of statistical filter such as a Kalman filter adaptedto operate also in the case where the measurement errors appearing inthe input data to the system have statistical distributions differentfrom those statistical distributions (e.g. a Gaussian distribution withzero mean value) that are currently assumed in standard statisticalfilter theory.

Such an arrangement is therefore adapted to provide optimal results alsoin those cases where errors statistical distribution is different fromthat typically assumed in the known prior art. Exemplary of such ascenario are those situations where location is based on the propagationtimes of signals from a terrestrial cellular network in an environmentaffected by multipath propagation effects. Under these circumstances,the measurement error exhibits an average value (mean value) that ishigher than zero and, therefore, can not lead to a Gaussian distributionwith zero mean value. This is due to multipath being a condition only toincrease—and not to reduce—propagation time with respect to the line ofsight.

Accordingly, in a preferred embodiment of the arrangement disclosedherein, a fictitious additional state is provided that is adapted torepresent such an error, having an higher than zero mean value, that isnot usually contemplated in the conventional theory of statisticalfilters such as the common Kalman filters. In particular, the methodaccording to present invention, enables the use of the kalmanstatistical filter in a cellular environment.

Moreover, the method enables to obtain good location results in a veryfast time. In fact, due to the use of the Kalman filter with a non zeromean error value, the method guarantees very good performances in termsof both accuracy and speed of convergence (i.e. time necessary toelaborate the measurements for calculating the position), up to ten timethe known solutions.

BRIEF DESCRIPTION OF THE ANNEXED DRAWINGS

The invention will now be described, by way of example only, withreference to the annexed figures of drawing, wherein:

FIG. 1 is a functional diagram depicting operation of a location systemas disclosed herein,

FIG. 2 is a block diagram disclosing the general arrangement of such asystem,

FIG. 3 is a flow chart representative of certain processing stepsperformed in the location system as disclosed herein, and

FIG. 4 schematically represents the possible application of thearrangement shown herein to a motor vehicle.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS OF THE INVENTION

By way of introduction to the description of an exemplary embodiment ofthe arrangement disclosed herein, some basic principles of Kalman filtertheory will be briefly summarized here. This is done by referringspecifically to the arrangement known as the so-called “Extended KalmanFilter” or, briefly, EKF.

Once again, it is worth recalling that reference to a Kalman filter isin no way intended to limit the scope of the invention that in factencompasses use of any statistical filter or predictor of a known type.

For the sake of simplicity, it will be assumed that the mobile terminalto be located is still (i.e. not in motion), and the additionalmeasurement provided to the location system is the altitude above sealevel of the terminal. The measurements provided by the terrestrialcellular networks are typically the propagation times of the radiofrequency signals.

According to basic EKF theory, such a scenario can be described asfollows.

$\begin{matrix}\left\{ \begin{matrix}{{\overset{\_}{x}}_{k + 1} = {{f\left( {\overset{\_}{x}}_{k} \right)} + {\overset{\_}{w}}_{k}}} \\{{\overset{\_}{y}}_{k} = {{h\left( {\overset{\_}{x}}_{k} \right)} + {\overset{\_}{e}}_{k}}} \\{{g\left( {\overset{\_}{x}}_{k} \right)} = {\overset{\_}{d}}_{k}}\end{matrix} \right. & (1)\end{matrix}$

The vector x is the unknown variable of the problem that is to beevaluated via the Kalman iterative process.

In the present case, the vector x includes:

-   -   the three coordinates x, y, z of the mobile terminal to be        located, and, additionally,    -   a further state t that represents the average error of the        network measurements y (terrestrial and/or satellite-based)        whereby        x _(k) =[x _(k) y _(k) z _(k) t _(k)]^(T)

Since the mobile terminal to be located is assumed to be still then onehas x _(k)= x _(k+1) and consequently f( x _(k))= x _(k).

The vector function h( x _(k)) describes those measurements that arecarried out that, in the case considered, correspond to the propagationtimes of the radio frequency signal from the base station. The functionh( x _(k)) is comprised of as many functions as the measurementsavailable at the k-th step and, for instance at the k-th step the i-thmeasurement y_(i,k) will give rise to the equation:y _(i,k) =h _(i)( x _(k))+ē _(k)=GeometricDistance(MobileTerminal_(step)_(—) _(k),BaseStation)+t _(k) +ē _(k)

where t_(k) describes the non-zero average value of the measurementerror e_(k).

Therefore, according to a feature of present invention, e_(k) is assumedas having a known distribution, i.e. a Gaussian distribution having azero average value, and t_(k) is assumed to be an unknown value to becalculated. In general t_(k) represents the non zero average value ofthe measurements both:

-   -   in case of additive errors;    -   in case of multiplicative errors.

The vector function g( x _(k))=d_(k) describes the constraints of thelocation system that render such a system more precise with respect tothe case where this additional information were not available. In theinstant case g(x_(k))=z_(k) (that is the altitude coordinate) and d_(k)is the altitude above sea level provided by means of an altimeter.

Finally, w _(k) and ē_(k) are two mutually independent Gaussianprocesses.

The system corresponding to equation (1) above is solved, by resortingto Kalman filter theory, by means of the iterative process described bythe following system indicated as (2). Specifically, the iterativeprocess starts from the initial condition {tilde over (x)}₀ and producesa sequence of solutions x _(k) gradually converging towards the positionof the system to be located.K _(k) =AH _(k)(H _(k) ^(T)Σ_(k) H _(k) +R)⁻¹{circumflex over (x)} _(k+1) =f({tilde over (x)} _(k) +K _(k)({rightarrow over (y)} _(k) −h({tilde over (x)} _(k))))+b(ũ _(k))Σ_(k+1) =F _(k)(I−K _(k) H ^(T))Σ_(k) F _(k) ^(T) +Q{tilde over (x)} _(k+1) ={circumflex over (x)} _(k+1)−Σ_(k+1) D ^(T)(DΣ_(k+1) D ^(T))⁻¹(D{circumflex over (x)} _(k+1) −p)  (2)

where H_(k) ^(T) is the matrix of the partial derivatives of thefunction h(x) evaluated for {right arrow over (x)}={circumflex over(x)}_(k);

F_(k) is the matrix of the partial derivatives of the function f({rightarrow over (x)}) evaluated for {right arrow over (x)}={circumflex over(x)}_(k); andD=g′({tilde over (x)} _(k+1)) and p=d−g({tilde over (x)}_(k+1))+g′({tilde over (x)} _(k+1)){tilde over (x)} _(k+1).

It will be appreciated that all of the foregoing is well known to thoseof skill in the art of statistical filters or predictors especially inconnection with Kalman filter theory, thereby making it unnecessary toprovide a more detailed description herein.

The location method considered in the foregoing is better shown in FIG.1.

FIG. 1 is comprised of functional diagram that is essentially similar toa flow chart identifying four basic phases comprising the methoddescribed herein, such basic phases being designated 1 to 4,respectively.

The phase designated 1 essentially involves extracting the informationnecessary for location purposes from:

-   -   a terrestrial cellular system T,    -   a satellite-based system S, and

other source of location information, generally designated A.

Such additional measurement sources may include the altitude information(i.e., the coordinate z) and/or (especially for applications in theautomotive field) measurements indicative of the distance traveled by amotorcar over a given time interval.

It will be appreciated that the criteria and methods for obtaining thosesignals are well known in the art, thus making it unnecessary to providea detailed description herein.

Reference 2 designates as a whole the phase wherein the initialconditions are estimated. Again, this occurs on the basis of methodsthat are well known in the art and, as such, are not significant for thepurpose of understanding the invention.

The further phase 3 includes those steps that comprise the processingengine proper for calculating the position at the k-th step.Essentially, the phase designated 3 comprises the statistic filterprocessing and can essentially be regarded as including:

-   -   a first step 100 wherein the covariance matrixes and the system        gain are updated,    -   a second step 102 wherein the system states are updated, and    -   a step 104 where the system states are filtered.

Finally, the phase designated 4 includes those steps that make theresults of the location action available to the client (i.e. the partyrequesting the location information).

These results may be in the form of “raw” position information fortracking on a geographic identification system (GIS) or any other formsof position display.

In the block diagram of FIG. 2, a mobile terminal MS is shownrepresenting the mobile terminal to be localized.

The mobile terminal MS is adapted to receive signals from a plurality ofsatellites Sat1, . . . , Satm together with additional information forimproving the accuracy of location action performed by the system.

To that purpose, the terminal MS includes a software module designatedPCF1, essentially intended to implement a positioning calculationfunction according to the invention.

The satellites designated Sat1, . . . , Satm transmit radio frequencysignals adapted to permit to the mobile terminal MS to compute thedistances of the mobile terminal MS to the various satellites.

The radio-frequency (radioelectric) signals transmitted from thesatellites also include information required for exactly determining thepositions of the satellite themselves. This occurs according towell-known criteria currently adopted in GPS systems of commercial typeor other satellite systems.

References SRB1, . . . SRBn designate a number of base stations (SRB orBTS) included in a terrestrial cellular communications system CA.

Those base stations transmit over the area covered by the network CAradio-frequency signals that permit the mobile terminal MS to computethe distance with respect to various base stations.

This occurs by means of power measurements (e.g. by measuring the signalpower received at the mobile terminal from the various base stations) orby measurements of entities such as timing advance (TA), round trip time(RTT), observed time differences (OTD), observed time differences ofarrival (OTDOA) and any other type of measurements currently availablein a terrestrial mobile radio network for locating the mobile terminalMS based on a method generally known in the art.

Of course, the positions of the base stations are known a priori andstored in a geographical data base.

An altimeter system provides data indicative of the altitude above thesea level of the mobile terminal MS to be localized.

The altimeter in question is exemplary of an additional measurementsystem (AMS) that may provide additional information adapted to renderthe location action significantly more precise. This in respect of boththe altitude coordinate z (which, of course, is an entity known veryprecisely, and not estimated) and the “plane” coordinates x and y,namely latitude and longitude.

Reference MLC designates as a whole a mobile location center adapted tocooperate with the mobile terminal MS via the mobile network CA.

The MLC system includes a bus-like arrangement of sub systems actingunder the coordination of a management system designated SM.

The subsystems typically include a gateway GW towards the IP (InternetProtocol) world, thus permitting a remote user U to request and obtainthe position of the mobile terminal MS. Such a function may be ofinterest for the delivery of so-called location based services (LBS) tothe user of mobile terminal MS.

Reference PCF2 designates a positioning calculating functionsubstantially duplicating the module PCF1 present in the mobile terminalMS for location purposes.

Reference MCG designates a communication management module currentlyassociated with the mobile network CA. Essentially, the module MCGperforms, for example, a number of tasks such as:

-   -   set-up the suitable communication (i.e., for example, Short        Message Service (SMS), or General Packet Radio Service (GPRS))        between the user U and the terminal MS;    -   transmit information through the network.

Finally, reference AB denotes an accounting and billing module.

The flow chart of FIG. 3 depicts the various steps that are carried outwhen the user in possession of mobile terminal MS decides, in a startstep 110, to activate the location procedure.

As a first step, designated 112, the terminal MS performs the variousmeasurements on the radioelectric signals received both from thesatellite network and from the terrestrial cellular network.

In a subsequent step 114, the mobile terminal MS collects the altitudeinformation from the AMS system.

Subsequently, the terminal MS transmits, via the module MCG, all themeasurements performed. This occurs in a step 116 that also leads themodule MCG, after verifying the identity of the user via the SM and ABmodules, to transfer the information received to the module PCF2.

In a step 118, the module PCF2 calculates the position of the mobileterminal MS and, via the module SM, re-transmits the results to themobile terminal by possibly informing the billing module AB.

At that point, in a step 120, the terminal MS may collect newmeasurements and therefore prompt an iterative process leading to theterminal MS being “tracked” over time by reporting the positioninformation just computed to the user.

When the location function is satisfactorily completed, the systemevolves to an end step 122.

In an alternative, at present preferred embodiment to the arrangementshown herein, the position of the mobile terminal is computed (step 116)with the mobile terminal itself, by exploiting the processing capabilityof the respective module designated PCF1.

Any mobile telecommunication terminal provided with a certain degree ofsignal processing availability (such as mobile terminals of theso-called “Smartphone” type) are equipped with sufficient dataprocessing power to perform such processing tasks.

If such a solution is adopted, the MLC system plays a support role byproviding the mobile terminal MS with information including e.g. thepositions of the base stations of the cellular network CA. Communicationtakes places via the MLC modules.

Still alternatively, the location action may not be prompted by the userin possession of the terminal MS but rather by a remote user U connectedvia the IP network.

In that case, the module GW permits such a remote user to access thelocation system after verifying its identity thereof via the module AB.At this point, acting under the supervision of the module SM, the systemMLC sends the request to perform the location action and report all themeasurements available to the mobile system MS by activating either ofthe functions PCF1 or PCF2 as soon as these measurements are received.

The results of location are then reported to the remote user U whilesimultaneously activating the billing module AB.

Such a location action prompted by a remote user U can be madesubservient to a specific authorization being granted positively by themobile terminal MS e.g. by the user pressing a given key in thatterminal. Still otherwise, for privacy purposes, the mobile terminal MSmay notify the system MLC that no request for location prompted by aremote user U should be processed by the system.

As previously indicated, several additional variants of the basicarrangement described previously can be easily conceived.

For instance a first variant provides for the possibility of dispensingwith any measurements carried with the support of the satellite-basedsystem. Essentially, this variant corresponds to deleting from the basiclayout of FIG. 1 the block designated S, while leaving in place bothblocks designated T (measurement from the terrestrial network) and A(other measurements system).

Another variant dispenses also with the information provided by theadditional measurements designated A. In that case, location isperformed on the basis of the sole information derived from theterrestrial system T.

Those of skill in the art will appreciate that those exemplified in theforegoing are just two of the many possible variants.

Any of the arrangements disclosed herein can be advantageously adoptedin an automotive scenario as schematically shown in FIG. 4. In thatfigure, reference M designates a vehicle such as a motorcar equippedwith a standard GPS receiver 201 as well as a terminal for terrestrialcellular mobile network 202. The vehicle M is also equipped withmeasurement system 203 adapted for measurement, e.g., the distancetraveled by the vehicle M over a given interval of time. All theelements considered in the foregoing are preferably connected via a busarrangement. This is preferably in the form of a so-called “CAN BUS”characterized with a high degree of robustness to environment noise.

Reference 204 designates a processing module essentially correspondingto the module designated PCF1 in FIG. 2. Such a module calculates theposition of the motor vehicle M by resorting to the method considered inthe foregoing based on the use of statistic filters. Finally, reference205 designates a system for managing location information preferablyincluding displayed unit adapted for presenting the result of thelocation action to the driver of the motor vehicle M.

Of course, without prejudice to the underlying principles of theinvention, the details and embodiments may vary, also significantly,with respect to what has been described by way of example only, withoutdeparting from the scope of the invention as defined by the annexedclaims.

1. A method for determining at least one location coordinate of a mobileterminal with respect to a set of reference elements adapted to sendradioelectric signals toward said mobile terminal, comprising the stepsof: measuring said radioelectric signals to derive respectivemeasurements, said measurements being affected by measurement errors;subjecting such respective measurements to state-based statisticalfiltering, said state-based statistical filtering comprising; selectingat least part of said set reference elements as terrestrial referenceelements; providing at least one first state representative of said atleast one location coordinate; providing at least one further state inaddition to said at least one first state, said at least one furtherstate being representative of said measurement errors having non-zeromean; and performing said state-based statistical filtering on saidrespective measurements, using said at least one first state and said atleast one further state in said state-based statistical filtering todetermine said at least one location coordinate of said mobile terminal.2. The method of claim 1, wherein said statistical filtering is Kalmanfiltering.
 3. The method of claim 1, comprising the step of associatingwith said respective measurements at least one additional measurementindicative of at least one of a location and displacement of said mobileterminal.
 4. The method of claim 3, comprising the step of measuring analtitude coordinate of said mobile terminal.
 5. The method of claim 1,comprising the step of including in said set of reference elements atleast one satellite-based reference element of a satellite-basedpositioning system.
 6. The method of claim 1, wherein measuring saidradioelectric signals comprises the step of determining at least oneparameter selected from the group consisting of: power received at saidmobile terminal from said set of reference elements, timing advance,round trip time, observed time differences, and observed timedifferences of arrival.
 7. The method of claim 1, comprising the step ofselecting at least part of said set of reference elements as elementscomprising, together with said mobile terminal, a terrestrial cellularcommunication system.
 8. A method for determining at least one locationcoordinate of a mobile terminal with respect to a set of referenceelements adapted to send radioelectric signals toward said mobileterminal, comprising the steps of: including in said set of referenceelements both terrestrial reference elements and at least onesatellite-based reference element of a satellite-based positioningsystem; measuring said radioelectric signals to derive respectivemeasurements, said measurements being affected by measurement errors;subjecting said respective measurements to state-based statisticalfiltering, said state-based statistical filtering comprising; providingat least one first state representative of said at least one locationcoordinate; providing at least one further state in addition to said atleast one first state, said at least one further state beingrepresentative of said measurement errors having non-zero mean;associating with said respective measurements at least one additionalmeasurement indicative of at least one of a location and displacement ofsaid mobile terminal; and performing said state-based statisticalfiltering on said respective measurements, using said at least one firststate and said at least one further state in said state-basedstatistical filtering to determine said at least one location coordinateof said mobile terminal.
 9. A system for determining at least onelocation coordinate of a mobile terminal with respect to a set ofreference elements adapted to send radioelectric signals toward saidmobile terminal, comprising: at least one measuring module for measuringsaid radioelectric signals and deriving respective measurements, saidrespective measurements being affected by measurement errors; and atleast one processing module adapted for performing state-basedstatistical filtering on said respective measurements, at least a partof said set of reference elements being terrestrial reference elements,and said at least one processing module being configured to: include insaid statistical filtering at least one first state representative ofsaid at least one location coordinate; include in said statisticalfiltering at least one further state in addition to said at least onefirst state, said at least one further state being representative ofsaid measurement errors having non-zero mean; and perform saidstate-based statistical filtering on said respective measurements usingsaid at least one first state and said at least one further state todetermine said at least one location coordinate of said mobile terminal.10. The system of claim 9, wherein said statistical filtering is Kalmanfiltering.
 11. The system of claim 9, comprising at least onemeasurement source providing at least one additional measurement to beassociated with said respective measurements, said at least oneadditional measurement being indicative of at least one of a locationand displacement of said mobile terminal.
 12. The system of claim 11,comprising an altimeter for measuring an altitude coordinate of saidmobile terminal.
 13. The system of claim 9, wherein said set ofreference elements comprises at least one satellite-based referenceelement of a satellite-based positioning system.
 14. The system of claim9, wherein said at least one measuring module is configured fordetermining at least one parameter selected from the group consistingof: power received at said mobile terminal from said set of referenceelements, timing advance, round trip time, observed time differences,and observed time differences of arrival.
 15. The system of claim 9,wherein at least part of said set of reference elements comprises,together with said mobile terminal, a terrestrial cellular communicationsystem.
 16. The system of claim 15, wherein at least one of saidmeasurement module and said processing module includes a first portionhosted by said mobile terminal and a second portion hosted by a locationcenter, wherein said first and second portions are arranged for dataexchange over said terrestrial cellular communication system.
 17. Asystem for determining at least one location coordinate of a mobileterminal with respect to a set of reference elements adapted to sendradioelectric signals toward said mobile terminal, comprising: both aset of terrestrial reference elements and at least one satellite-basedreference element of a satellite-based positioning system as saidreference elements; at least one measuring module for measuring saidradioelectric signals to derive respective measurements, said respectivemeasurements being affected by measurement errors; at least oneprocessing module configured to perform state-based statisticalfiltering on said respective measurements, wherein the at least oneprocessing module: includes in said statistical filtering at least onefirst state representative of said at least one location coordinate,includes in said statistical filtering at least one further state inaddition to said at least one first state, said at least one furtherstate being representative of said measurement errors having non-zeromean, and performs said state-based statistical filtering on saidrespective measurements using said at least one first state and said atleast one further state to determine said at least one locationcoordinate of said mobile terminal; and at least one measurement sourceproviding at least one additional measurement to be associated with saidrespective measurements, said at least one additional measurement beingindicative of at least one of a location and displacement of said mobileterminal.
 18. A mobile terminal configured for determining its locationcoordinates with respect to a set of reference elements adapted to sendradioelectric signals toward said mobile terminal, comprising: ameasuring module for measuring said radioelectric signals and derivingrespective measurements, said respective measurements being affected bymeasurement errors; and a processing module adapted for performingstate-based statistical filtering on said respective measurements, themobile terminal comprising together with at least part of said set ofreference elements, a terrestrial communication system, and saidprocessing module being configured to: include in said statisticalfiltering at least one first state representative of said locationcoordinates, include in said statistical filtering at least one furtherstate in addition to said at least one first state, said at least onefurther state being representative of said measurement errors havingnon-zero mean, and perform said state-based statistical filtering onsaid respective measurements using said at least one first state andsaid at least one further state to determine said location coordinatesof said mobile terminal.
 19. The mobile terminal of claim 18, whereinsaid statistical filtering is Kalman filtering.
 20. The mobile terminalof claim 18, wherein said mobile terminal has at least one measurementsource providing at least one additional measurement to be associatedwith said respective measurements, said at least one additionalmeasurement being indicative of at least one of a location anddisplacement of said mobile terminal.
 21. The mobile terminal of claim20, wherein said mobile terminal has an altimeter for measuring analtitude coordinate of said mobile terminal.
 22. The mobile terminal ofclaim 20, wherein said mobile terminal is mounted on a vehicle, and saidat least one additional measurement is indicative of at least one of alocation and displacement of said vehicle.
 23. The mobile terminal ofclaim 18, wherein said measuring module is configured for determining atleast one parameter selected from the group consisting of: powerreceived at said mobile terminal from said set of reference elements,timing advance, round trip time, observed time differences and observedtime differences of arrival.
 24. A mobile terminal configured fordetermining its location coordinates with respect to a set of referenceelements adapted to send radioelectric signals toward said mobileterminal, said set of reference elements including both terrestrialreference elements and at least one satellite-based reference element ofa satellite-based positioning system, said mobile terminal comprising: ameasuring module for measuring said radioelectric signals to deriverespective measurements, said respective measurements being affected bymeasurement errors; a processing module configured to performstate-based statistical filtering on said respective measurements,wherein the processing module: includes in said statistical filtering atleast one first state representative of said location coordinates,includes in said statistical filtering at least one further state inaddition to said at least one first state, said at least one furtherstate being representative of said measurement errors having non-zeromean, and performs said state-based statistical filtering on saidrespective measurements using said at least one first state and said atleast one further state to determine said location coordinates of saidmobile terminal; and at least one measurement source associated to saidmobile terminal and providing at least one additional measurement to beassociated with said respective measurements, said at least oneadditional measurement being indicative of at least one of a locationand displacement of said mobile terminal.
 25. A non-transitory computerreadable medium encoded with a computer program product loadable into amemory of at least one computer, the computer program product comprisingsoftware code portions for performing the method of any one of claims 1to
 8. 26. A non-transitory computer readable medium encoded with acomputer program product loadable into a memory of a computer andincluding software code portions for implementing the mobile terminal ofany one of claims 18 to 24.